activity
20082026
most citedFederated Learning of N-gram Language Models

18 citations · 41 across the 15 of their papers we have counts for

collaborators

16 papers

cs.CV2026

Gemini Embedding 2: A Native Multimodal Embedding Model from Gemini

Madhuri Shanbhogue, Zhe Li, Shanfeng Zhang +86

We introduce Gemini Embedding 2, a native multimodal embedding model that allows embedding video, audio, image, and text modalities in a unified representation space. We leverage t…

cs.SD2026

Benchmarking LLMs on the Massive Sound Embedding Benchmark (MSEB)

Cyril Allauzen, Tom Bagby, Georg Heigold +2

The Massive Sound Embedding Benchmark (MSEB) has emerged as a standard for evaluating the functional breadth of audio models. While initial baselines focused on specialized encoder…

cs.SD2026★ 1 cited

Massive Sound Embedding Benchmark (MSEB)

Georg Heigold, Ehsan Variani, Tom Bagby +4

Audio is a critical component of multimodal perception, and any truly intelligent system must demonstrate a wide range of auditory capabilities. These capabilities include transcri…

cs.FL2025

Tutorial: -Transductions in OpenFst via the Gallic Semiring

Marco Cognetta, Cyril Allauzen

OpenFst, a popular finite-state transducer library, supports -transitions but, due to an implementation constraint, they cannot be used with transducers in a straightforward way…

cs.CL2024★ 1 cited

Multilingual and Fully Non-Autoregressive ASR with Large Language Model Fusion: A Comprehensive Study

W. Ronny Huang, Cyril Allauzen, Tongzhou Chen +7

In the era of large models, the autoregressive nature of decoding often results in latency serving as a significant bottleneck. We propose a non-autoregressive LM-fused ASR system…

eess.AS2023

Large-scale Language Model Rescoring on Long-form Data

Tongzhou Chen, Cyril Allauzen, Yinghui Huang +8

In this work, we study the impact of Large-scale Language Models (LLM) on Automated Speech Recognition (ASR) of YouTube videos, which we use as a source for long-form ASR. We demon…